1. Field of the Invention
The present invention is related to a method and system for using wavelet analysis to evaluate a signal generated by a fractal system and more particularly to a method and system for evaluating an Electrocardiogram ("ECG") signal to detect persons having heart disease or those who are at risk for ventricular tachycardia ("VT") or sudden death.
2. Description of the Prior Art
It is known that some systems are ideally comprised of fractals. Fractals are geometric shapes whose structure is such that magnification by a given factor reproduces the original object. However, if such a system also comprises and multifractals, the system may contain abnormalities in its fractal structure which are indicative of problems in the system.
For example, the conduction system of a healthy human heart is considered to be comprised of fractals where fractal systems have the same dimension and scaling law throughout. In a multifractal system the scaling law is different at different points. Since the conduction system of the human heart is comprised of fractals, the system should have the same dimension and scaling law throughout. Indeed, the most common substrate for ventricular tachycardia after a myocardial infarction is a local scar, which should have a multifractal structure. The substrate for ventricular tachycardia has been thought to have increased dispersion of refractoriness where this increased dispersion can lead to the possibility of the electrical signal entering reentrant loops, which lead to ventricular tachycardia or sudden death. Thus, to evaluate whether a human heart is considered to be healthy, the fractal system could be evaluated to determine if it includes multifractals. It is difficult, however, to determine whether a system is a non-ideal fractal system, i.e., comprised of fractal and multifractals. As a consequence, other techniques have been developed to evaluate signals produced by non-ideal fractal systems.
In particular, systems and methods have been developed to evaluate particular regions of an ECG signal using filtering techniques. It has been found that certain frequency characteristics in an electrocardiogram ("ECG") signal may indicate the presence of late potentials ("LP"). It has been found that by evaluating the portion of an ECG immediately following the Q, R, and S waves ("QRS") (also known as the ventricular depolarization complex) for the presence of particular high frequency components, LPs could be determined in certain patients. Such a technique is described in U.S. Pat. No. 4,422,459 to Simson, which is hereby incorporated by reference. Another technique uses a moving, short window FFT to analyze an ECG signal for diagnostic purposes. Such a technique is described in U.S. Pat. No. 5,046,504 to Albert et al., which is also hereby incorporated by reference. Unfortunately, known techniques have not been found effective at detecting the presence of all types of heart disease or patients at risk for VT or sudden death. Instead, existing techniques generally focus on detecting the presence of LPs.
Accordingly, present invention is designed to permit a more rigorous evaluation of signals from fractal systems, such as the conduction system of the heart, so that additional characteristics of the system may be recognized and diagnosed.